Pulse generators, such as pacemakers and implantable cardiac defibrillators, record numerous electrograms associated with arrhythmic events or episodes. More than one type of arrhythmia may fall within a single detection zone for a patient. Thus, a clinician needs to inspect the recorded electrograms to assess a cause of each arrhythmia. Further, the same arrhythmia may occur many times in the same patient, leading to the presentation of many occurrences of the same condition for a clinician to review.
Some patient management systems include entire collections of episodes recorded for patients since device implant. This data is made available for user assessment via user interfaces. Reviewing hundreds of recorded episodes to assess patient trends can be tedious and time consuming for clinicians. Other factors, such as assessing recorded heart rates, values of detection-related variables, and the quantity and types of therapies delivered can also contribute to user data overload.
Some conventional programmer applications reduce the number of displayed arrhythmic events by filtering based on initial detection zone or by range of dates. However, this approach does not distinguish between different arrhythmias in the same zone or the same type of arrhythmia detected in different zones.
Accordingly there is an unaddressed need in the industry to address the aforementioned and other deficiencies and inadequacies.